code: def test_log_marginal_likelihood_with_small_ensemble_no_perturb_obs(
      self,
  ):
      # With perturbed_observations=False, we should be able to handle the small
      # ensemble without NaN.
  
      # Initialize an ensemble with that is smaller than the event size.
      seed_stream = test_util.test_seed_stream()
      n_ensemble = 3
      event_size = 5
      self.assertLess(n_ensemble, event_size)
      particles_shape = (n_ensemble, event_size)
  
      particles = {
          "x": self.evaluate(
              tf.random.normal(
                  shape=particles_shape, seed=seed_stream()
              )
          ),
      }
  
      def observation_fn(_, particles, extra):
          return (
              mvn_diag.MultivariateNormalDiag(
                  loc=particles["x"], scale_diag=[1e-2] * event_size
              ),
              extra,
          )
  
      # Marginal likelihood.
      log_ml = ekf.ensemble_kalman_filter_log_marginal_likelihood(
          state=ekf.EnsembleKalmanFilterState(
              step=0, particles=particles, extra={}
          ),
          observation=tf.random.normal(
              shape=(event_size,), seed=seed_stream()
          ),
          observation_fn=observation_fn,
          perturbed_observations=False,
          seed=test_util.test_seed(),
      )
      self.assertAllEqual(particles_shape[1:-1], log_ml.shape)
      self.assertFalse(np.any(np.isnan(self.evaluate(log_ml))))
  
imports: import collections
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import joint_distribution_named
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import mvn_tril
  from tensorflow_probability.python.distributions import poisson
  from tensorflow_probability.python.experimental.sequential import ensemble_kalman_filter
  from tensorflow_probability.python.internal import test_combinations
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.stats import sample_stats
label_desc: Use image node_id 6 for calling the EnsembleKalmanFilterTest obj's underlying member method code with example usage: obj.test_log_marginal_likelihood_with_small_ensemble_no_perturb_obs() and returns: mvn_diag,  extra